Using Reporting Guidelines to Draft Research Articles: A Step-by-Step Guide

Writing guides help researchers write quickly and confidently by breaking up the writing process into manageable pieces, and by detailing the information their readers will need to fully understand, apply, and appraise research.

Published

March 27, 2025

The writing process

If you have ever taken a holiday, you will know there is a good way and a bad way to pack a suitcase.

The bad way is to fling things in, as and when you think of them. Rushed and stressed, the disorganised packer struggles to close their bloated bag and upon unpacking, their clothes are creased, possessions jumbled, and their toothbrush is forgotten at home.

An organised packer has a process. Often this begins with a list, laying everything out in front of you, then carefully deciding which items belong in the suitcase, which will go in carry-on, and how clothes can be folded to minimise space and creasing. The organised packer feels relaxed and enjoys their journey in the confidence that they’ve forgotten nothing.

Writing academic articles is a lot like packing a suitcase. The author has to cram a lot of information into a small space, without crumpling the message they are trying to convey. Reporting guidelines act as the packing list, and the process we describe below covers the act of collating your stuff (information), laying it out (on the page), deciding what goes where (reorganising), and then finally, packing (writing a first draft).

Step 1: Get the appropriate writing guide

Download the writing guide for the reporting guideline that matches your study design. For reporting guidelines not featured on this website, you can make your own writing guide based on their available resources by searching our database.

Step 2: Collate information

Gather your research materials (e.g., your notes, data, analyses, protocol)

For each section in the writing guide:

  • Note answers to all prompting questions
  • Document any information that cannot be included and why
  • Identify information that would benefit from visual presentation.
    • Draft tables.
    • Collate figures that already exist. If custom figures need to be made, note down what information they should convey.

Step 3: Content Organization and Prioritization

By now you may already have a target journal in mind. Review their author instructions for word limits, figure/table allowances, and supplementary material policies.

Begin reorganising your notes into a structure that fits your narrative and priorities. You might prefer to do this in a new document, or to delete the provided writing guide section titles and prompts. Group your notes into paragraphs. Some authors like to assign word limits to paragraphs or sections at this stage. Consider adding topic and linking sentences to the start and end of each paragraph. This helps creates flow.

When organising content, consider how important the information will be to most of your readers. Prioritise information you expect most readers will find important. Content you expect only a small section of your audience will seek out can be placed later in your writing, allocated less space or, if necessary, be placed in supplementary material. Do not delete any information – although you may consider it unimportant, every item in a reporting guideline is important to somebody.

By now, your notes should be grouped into paragraphs, separated into main text and supplementary materials, and be filled with all of the information, data, and sources you’ll need to write. You should have drafted your tables and planned your figures.

Tip

Now is a good moment to talk a colleague through your outline. Your notes will be brief and rough, but someone familiar with the work will be able to give feedback on your proposed structure and content.

Step 4: Writing the First Draft

Once you are ready to start drafting, open a new document. Your writing guide is probably very long by now, so writing in a new document means you can maintain focus without deleting notes.

We suggest you begin by drafting the Methods section as this is generally the easiest to get started with, then the Results before the Introduction, Discussion and, finally, the Abstract and Title. When drafting, try not to use your delete key. The aim is get words on the page, no matter how messy they are. If you get stuck on something, consider using a placeholder (like #TODO) and come back to it later.

Tip

This is another good moment to get feedback from colleagues. Give them your manuscript and ask whether the structure and flow make sense. Because it’s only a first draft, you may want to ask them to not worry about spelling, grammar, or conciseness.

Step 5: Revision and editing

Review the draft for logical flow between sections.

Edit your text to make it clear, concise and engaging.

Once the text is ready to submit, complete the reporting checklist for the reporting guideline you used.

Tip

This is an opportunity for a final round of feedback from a colleague. You may want to ask them to do a more through edit of your writing, fixing any errors and reworking sentences for clarity and conciseness. Consider asking a colleague to complete the reporting checklist on their own as part of this review, or to look through the checklist you already completed. This will allow you to check whether your interpretation of the guidance requirements matches theirs, and whether you have presented information clearly.

Add the completed reporting checklist as a supplement, and ensure you have credited the reporting guideline, checklist, and writing guide.

Submission

Include your completed reporting checklist as a supplement when you submit to your chosen journal. If your target journal/funder do not accept supplementary material, you can upload your checklist to a repository like the OSF and cite it.

Training and resources

The EQUATOR Network provides training on writing research articles and applications. We have training on:

  • Writing processes
  • Concise, clear, and compelling writing
  • Writing using reporting guidelines

Reporting Guidelines are recommendations to help describe your work clearly

Your research will be used by people from different disciplines and backgrounds for decades to come. Reporting guidelines list the information you should describe so that everyone can understand, replicate, and synthesise your work.

Reporting guidelines do not prescribe how research should be designed or conducted. Rather, they help authors transparently describe what they did, why they did it, and what they found.

Reporting guidelines make writing research easier, and transparent research leads to better patient outcomes.

Easier writing

Following guidance makes writing easier and quicker.

Smoother publishing

Many journals require completed reporting checklists at submission.

Maximum impact

From nobel prizes to null results, articles have more impact when everyone can use them.

Who reads research?

You work will be read by different people, for different reasons, around the world, and for decades to come. Reporting guidelines help you consider all of your potential audiences. For example, your research may be read by researchers from different fields, by clinicians, patients, evidence synthesisers, peer reviewers, or editors. Your readers will need information to understand, to replicate, apply, appraise, synthesise, and use your work.

Cohort studies

A cohort study is an observational study in which a group of people with a particular exposure (e.g. a putative risk factor or protective factor) and a group of people without this exposure are followed over time. The outcomes of the people in the exposed group are compared to the outcomes of the people in the unexposed group to see if the exposure is associated with particular outcomes (e.g. getting cancer or length of life).

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Case-control studies

A case-control study is a research method used in healthcare to investigate potential risk factors for a specific disease. It involves comparing individuals who have been diagnosed with the disease (cases) to those who have not (controls). By analysing the differences between the two groups, researchers can identify factors that may contribute to the development of the disease.

An example would be when researchers conducted a case-control study examining whether exposure to diesel exhaust particles increases the risk of respiratory disease in underground miners. Cases included miners diagnosed with respiratory disease, while controls were miners without respiratory disease. Participants' past occupational exposures to diesel exhaust particles were evaluated to compare exposure rates between cases and controls.

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Cross-sectional studies

A cross-sectional study (also sometimes called a "cross-sectional survey") serves as an observational tool, where researchers capture data from a cohort of participants at a singular point. This approach provides a 'snapshot'— a brief glimpse into the characteristics or outcomes prevalent within a designated population at that precise point in time. The primary aim here is not to track changes or developments over an extended period but to assess and quantify the current situation regarding specific variables or conditions. Such a methodology is instrumental in identifying patterns or correlations among various factors within the population, providing a basis for further, more detailed investigation.

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Systematic reviews

A systematic review is a comprehensive approach designed to identify, evaluate, and synthesise all available evidence relevant to a specific research question. In essence, it collects all possible studies related to a given topic and design, and reviews and analyses their results.

The process involves a highly sensitive search strategy to ensure that as much pertinent information as possible is gathered. Once collected, this evidence is often critically appraised to assess its quality and relevance, ensuring that conclusions drawn are based on robust data. Systematic reviews often involve defining inclusion and exclusion criteria, which help to focus the analysis on the most relevant studies, ultimately synthesising the findings into a coherent narrative or statistical synthesis. Some systematic reviews will include a meta-analysis.

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Systematic review protocols

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Meta analyses of Observational Studies

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Randomised Trials

A randomised controlled trial (RCT) is a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo. The groups are then followed up to see if there are any differences between the results. This helps in assessing the effectiveness of the intervention.

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Randomised Trial Protocols

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Qualitative research

Research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behavior. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis.

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Case Reports

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Diagnostic Test Accuracy Studies

Diagnostic accuracy studies focus on estimating the ability of the test(s) to correctly identify subjects with a predefined target condition, or the condition of interest (sensitivity) as well as to clearly identify those without the condition (specificity).

Prediction Models

Prediction model research is used to test the accurarcy of a model or test in estimating an outcome value or risk. Most models estimate the probability of the presence of a particular health condition (diagnostic) or whether a particular outcome will occur in the future (prognostic). Prediction models are used to support clinical decision making, such as whether to refer patients for further testing, monitor disease deterioration or treatment effects, or initiate treatment or lifestyle changes. Examples of well known prediction models include EuroSCORE II for cardiac surgery, the Gail model for breast cancer, the Framingham risk score for cardiovascular disease, IMPACT for traumatic brain injury, and FRAX for osteoporotic and hip fractures.

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Animal Research

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Quality Improvement in Healthcare

Quality improvement research is about finding out how to improve and make changes in the most effective way. It is about systematically and rigourously exploring "what works" to improve quality in healthcare and the best ways to measure and disseminate this to ensure positive change. Most quality improvement effectiveness research is conducted in hospital settings, is focused on multiple quality improvement interventions, and uses process measures as outcomes. There is a great deal of variation in the research designs used to examine quality improvement effectiveness.

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Economic Evaluations in Healthcare

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Meta Analyses

A meta-analysis is a statistical technique that amalgamates data from multiple studies to yield a single estimate of the effect size. This approach enhances precision and offers a more comprehensive understanding by integrating quantitative findings. Central to a meta-analysis is the evaluation of heterogeneity, which examines variations in study outcomes to ensure that differences in populations, interventions, or methodologies do not skew results. Techniques such as meta-regression or subgroup analysis are frequently employed to explore how various factors might influence the outcomes. This method is particularly effective when aiming to quantify the effect size, odds ratio, or risk ratio, providing a clearer numerical estimate that can significantly inform clinical or policy decisions.

How Meta-analyses and Systematic Reviews Work Together

Systematic reviews and meta-analyses function together, each complementing the other to provide a more robust understanding of research evidence. A systematic review meticulously gathers and evaluates all pertinent studies, establishing a solid foundation of qualitative and quantitative data. Within this framework, if the collected data exhibit sufficient homogeneity, a meta-analysis can be performed. This statistical synthesis allows for the integration of quantitative results from individual studies, producing a unified estimate of effect size. Techniques such as meta-regression or subgroup analysis may further refine these findings, elucidating how different variables impact the overall outcome. By combining these methodologies, researchers can achieve both a comprehensive narrative synthesis and a precise quantitative measure, enhancing the reliability and applicability of their conclusions. This integrated approach ensures that the findings are not only well-rounded but also statistically robust, providing greater confidence in the evidence base.

Why Don't All Systematic Reviews Use a Meta-Analysis?

Systematic reviews do not always have meta-analyses, due to variations in the data. For a meta-analysis to be viable, the data from different studies must be sufficiently similar, or homogeneous, in terms of design, population, and interventions. When the data shows significant heterogeneity, meaning there are considerable differences among the studies, combining them could lead to skewed or misleading conclusions. Furthermore, the quality of the included studies is critical; if the studies are of low methodological quality, merging their results could obscure true effects rather than explain them.

Protocol

A plan or set of steps that defines how something will be done. Before carrying out a research study, for example, the research protocol sets out what question is to be answered and how information will be collected and analysed.

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